This repository was created for people who will attend the Data Science Summit tutorial. This tutorial is based on OpenCV version 3.1.0.
To install OpenCVP please follow the instructions in the markdown file "Installation Steps for OpenCV 3.1.0"
- Author: Rodrigo Agundez from Qualogy
- Place: Jerusalem, International Convention Center
- Date: Sunday, June 5, 2016
- Time: 10:00
- Room: 1
The goal of this tutorial is to build a simple face recognition system with the use of the opencv library. This tutorial is separated in four parts:
- Manipulation of images and videos using OpenCV.
- Face Detection and Buildig the dataset
- Building the recognition model
- Recognize faces in a live video feed
OpenCV is an open source computer vision and machine learning software library. The library includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to:
- Detect Faces
- Recognize Faces
- Identify Objects
- Classify human actions in videos
- Track camera movement
- Track moving objects
- Extract 3D models of objects
- Produce 3D point clouds from stereo cameras
- Stitch images together to produce a high resolution image of an entire scene
- Find similar images from an image database
- Remove red eyes from images taken using flash
- Follow eye movements
It has C++, C, Python, Java and MATLAB interfaces and supports Windows, Linux, Android and Mac OS.